Persistent Homology of Attractors For Action Recognition

In this paper, we propose a novel framework for dynamical analysis of human actions from 3D motion capture data using topological data analysis. We model human actions using the topological features of the attractor of the dynamical system. We reconstruct the phase-space of time series corresponding to actions using time-delay embedding, and compute the persistent homology of the phase-space reconstruction. In order to better represent the topological properties of the phase-space, we incorporate the temporal adjacency information when computing the homology groups. The persistence of these homology groups encoded using persistence diagrams are used as features for the actions. Our experiments with action recognition using these features demonstrate that the proposed approach outperforms other baseline methods.Comment: 5 pages, Under review in International Conference on Image Processin

A semidiscrete version of the Citti-Petitot-Sarti model as a plausible model for anthropomorphic image reconstruction and pattern recognition

In his beautiful book [66], Jean Petitot proposes a sub-Riemannian model for the primary visual cortex of mammals. This model is neurophysiologically justified. Further developments of this theory lead to efficient algorithms for image reconstruction, based upon the consideration of an associated hypoelliptic diffusion. The sub-Riemannian model of Petitot and Citti-Sarti (or certain of its improvements) is a left-invariant structure over the group $SE(2)$ of rototranslations of the plane. Here, we propose a semi-discrete version of this theory, leading to a left-invariant structure over the group $SE(2,N)$, restricting to a finite number of rotations. This apparently very simple group is in fact quite atypical: it is maximally almost periodic, which leads to much simpler harmonic analysis compared to $SE(2).$ Based upon this semi-discrete model, we improve on previous image-reconstruction algorithms and we develop a pattern-recognition theory that leads also to very efficient algorithms in practice.Comment: 123 pages, revised versio

M\"obius Invariants of Shapes and Images

Identifying when different images are of the same object despite changes caused by imaging technologies, or processes such as growth, has many applications in fields such as computer vision and biological image analysis. One approach to this problem is to identify the group of possible transformations of the object and to find invariants to the action of that group, meaning that the object has the same values of the invariants despite the action of the group. In this paper we study the invariants of planar shapes and images under the M\"obius group $\mathrm{PSL}(2,\mathbb{C})$, which arises in the conformal camera model of vision and may also correspond to neurological aspects of vision, such as grouping of lines and circles. We survey properties of invariants that are important in applications, and the known M\"obius invariants, and then develop an algorithm by which shapes can be recognised that is M\"obius- and reparametrization-invariant, numerically stable, and robust to noise. We demonstrate the efficacy of this new invariant approach on sets of curves, and then develop a M\"obius-invariant signature of grey-scale images

Neural correlates of consciousness are not pictorial representations

O'Regan & Noe (O&N) are pessimistic about the prospects for discovering the neural correlates of consciousness. They argue that there can be no one-to-one correspondence between awareness and patterns of neural activity in the brain, so a project attempting to identify the neural correlates of consciousness is doomed to failure. We believe that this degree of pessimism may be overstated; recent empirical data show some convergence in describing consistent patterns of neural activity associated with visual consciousness

Toward an ecological conception of timbre

This paper is part of a series in which we had worked in the last 6 months, and, specifically, intend to investigate the notion of timbre through the ecological perspective proposed by James Gibson in his Theory of Direct Perception. First of all, we discussed the traditional approach to timbre, mainly as developed in acoustics and psychoacoustics. Later, we proposed a new conception of timbre that was born in concepts of ecological approach. The ecological approach to perception proposed by Gibson (1966, 1979) presupposes a level of analysis of perceptual stimulated that includes, but is quite broader than the usual physical aspect. Gibson suggests as focus the relationship between the perceiver and his environment. At the core of this approach, is the notion of affordances, invariant combinations of properties at the ecological level, taken with reference to the anatomy and action systems of species or individual, and also with reference to its biological and social needs. Objects and events are understood as relates to a perceiving organism by the meaning of structured information, thus affording possibilities of action by the organism. Event perception aims at identifying properties of events to specify changes of the environment that are relevant to the organism. The perception of form is understood as a special instance of event perception, which is the identity of an object depends on the nature of the events in which is involved and what remains invariant over time. From this perspective, perception is not in any sense created by the brain, but is a part of the world where information can be found. Consequently, an ecological approach represents a form of direct realism that opposes the indirect realist based on predominant approaches to perception borrowed from psychoacoustics and computational approach